Systems and methods for predicting the health of integrated drive generators

1. A method of predicting a health status of an integrated drive generator (IDG), the method comprising: determining an effective deviation across a plurality of IDG output frequencies for a given IDG operation period; and correlating the effective deviation to an IDG capability to determine a health of the IDG, wherein determining the effective deviation includes isolating the IDG output frequencies when a respective IDG speed is within a tolerance about a straight-through speed of the IDG to generate a plurality of isolated output frequencies, wherein determining the effective deviation includes determining a modified mean output frequency for the given IDG operation period across a plurality of select output frequencies of the plurality of output frequencies, and wherein determining the effective deviation includes determining a delta frequency for each isolated output frequency, wherein the delta isolated output frequency is a difference between a given one of the isolated output frequencies and the modified mean output frequency.

2. The method as recited in claim 1 , wherein the IDG capability is a near-term remaining useful life (RUL) prediction, wherein the method includes outputting a health assessment if the near-term RUL prediction is equal to or less than a threshold.

3. The method as recited in claim 2 , wherein the threshold includes at least one warning threshold, wherein outputting the health assessment includes outputting at least one warning if the near-term RUL prediction is equal to or less than the at least one warning threshold.

4. The method as recited in claim 2 , wherein the threshold includes a series of multiple warning thresholds, wherein outputting the health assessment includes outputting at least one of a series of warnings if the near-term RUL prediction is equal to or less than one or more of the series of warning thresholds.

5. The method as recited in claim 4 , wherein outputting the at least one of the series of warnings includes scheduling an IDG maintenance action.

6. The method as recited in claim 5 , wherein the IDG maintenance action includes at least one of repair, replacement, or stocking parts for at least one of repair or replacement.

7. The method as recited in claim 1 , further comprising adding the effective deviation to a historical database for an IDG.

8. The method as recited in claim 1 , wherein determining the effective deviation includes determining a modified mean output frequency for the given IDG operation period across a plurality of select output frequencies of the plurality of output frequencies.

9. The method as recited in claim 8 , wherein the select output frequencies are outside of a tolerance about a straight-through speed of the IDG.

10. The method as recited in claim 1 , wherein determining the effective deviation includes determining an effective standard deviation by generating a root mean squared (RMS) value for the delta frequencies.

11. The method as recited in claim 1 , wherein determining the effective deviation includes determining an effective statistical percentile deviation and determining a modified mean output frequency for the given IDG operation period across a plurality of select output frequencies of the plurality of output frequencies, wherein the effective statistical percentile deviation is the difference between one of the isolated frequencies at a given percentile and the modified mean output frequency.

12. A system for predicting a health status of an integrated drive generator (IDG), the system comprising: an IDG; a generator control unit (GCU) operatively connected to the IDG to determine a plurality of IDG output frequencies for a given IDG operation period; and a central processing unit (CPU) operatively connected to the GCU to receive the IDG output frequencies therefrom, wherein the CPU is configured and adapted to determine an effective deviation across at least some of the plurality of IDG output frequencies for the given IDG operation period, and correlate the effective deviation to an IDG capability to determine a health of the IDG, wherein determining the effective deviation includes isolating the IDG output frequencies when a respective IDG speed is within a tolerance about a straight-through speed of the IDG to generate a plurality of isolated output frequencies, wherein determining the effective deviation includes determining a modified mean output frequency for the given IDG operation period across a plurality of select output frequencies of the plurality of output frequencies, and wherein determining the effective deviation includes determining a delta frequency for each isolated output frequency, wherein the delta isolated output frequency is a difference between a given one of the isolated output frequencies and the modified mean output frequency.

13. The system as recited in claim 12 , wherein the IDG capability is a near-term RUL prediction.

14. The system as recited in claim 13 , further comprising a historical database configured and adapted to store the effective deviation.

15. The system as recited in claim 12 , wherein the CPU includes an input configured and adapted to receive engine speed data.

16. The system as recited in claim 12 , wherein the CPU includes an output configured and adapted to send a near-term RUL prediction as a health assessment output and trigger a maintenance action.

17. The system as recited in claim 16 , wherein the maintenance action includes at least one of repair, replacement, or stocking parts for at least one of repair or replacement.